generate-statistical-tables

name	generate-statistical-tables
description	Generate publication-ready statistical tables using gt, kableExtra, or flextable. Covers descriptive statistics, regression results, ANOVA tables, correlation matrices, and APA formatting. Use when creating descriptive statistics tables, formatting regression or ANOVA output, building correlation matrices, producing APA-style tables for academic papers, or generating tables for Quarto and R Markdown documents.
license	MIT
allowed-tools	Read Write Edit Bash Grep Glob
metadata	{"author":"Philipp Thoss","version":"1.0","domain":"reporting","complexity":"intermediate","language":"R","tags":"r, tables, gt, statistics, publication"}

Generate Statistical Tables

Create publication-ready statistical tables for reports and manuscripts.

When to Use

• Creating descriptive statistics tables
• Formatting regression or ANOVA output
• Building correlation matrices
• Producing APA-style tables for academic papers
• Generating tables for Quarto/R Markdown documents

Inputs

• Required: Statistical analysis results (model objects, summary data)
• Required: Output format (HTML, PDF, Word)
• Optional: Style guide (APA, journal-specific)
• Optional: Table numbering scheme

Procedure

Step 1: Choose Table Package

Package	Best for	Formats
gt	HTML, general-purpose	HTML, PDF, Word
kableExtra	LaTeX/PDF documents	PDF, HTML
flextable	Word documents	Word, PDF, HTML
gtsummary	Clinical/statistical summaries	All via gt/flextable

Expected: A table package selected based on the output format and use case. The chosen package is installed and loadable.

On failure: If the required package is not installed, run install.packages("gt") (or the appropriate package). For gtsummary, both gt and gtsummary must be installed.

Step 2: Descriptive Statistics Table

library(gt)

descriptives <- data |>
  group_by(group) |>
  summarise(
    n = n(),
    M = mean(score, na.rm = TRUE),
    SD = sd(score, na.rm = TRUE),
    Min = min(score, na.rm = TRUE),
    Max = max(score, na.rm = TRUE)
  )

gt(descriptives) |>
  tab_header(
    title = "Table 1",
    subtitle = "Descriptive Statistics by Group"
  ) |>
  fmt_number(columns = cM SD decimals   
  fmt_numbercolumns  Min Max decimals   
  cols_label
    group  
    n  md
    M  md
    SD  md
  

Expected: A gt table object with formatted means, SDs, and counts grouped by category. Column headers use proper statistical notation (italicized M, SD, n).

On failure: If group_by() produces unexpected results, verify the grouping variable exists and has the expected levels. If fmt_number() throws an error, ensure the target columns contain numeric data.

Step 3: Regression Results Table

model <- lm(outcome ~ predictor1 + predictor2 + predictor3, data = data)

library(gtsummary)

tbl_regression(model) |>
  bold_p() |>
  add_glance_source_note(
    include = c(r.squared, adj.r.squared, nobs)
  ) |>
  modify_header(label = "**Predictor**") |>
  modify_caption("Table 2: Regression Results")

Expected: A gtsummary regression table with bolded p-values, model fit statistics (R-squared, N) in a source note, and a descriptive caption.

On failure: If tbl_regression() fails, verify the input is a model object (e.g., lm, glm). If add_glance_source_note() errors, check that broom can tidy the model: broom::glance(model).

Step 4: Correlation Matrix

library(gt)

cor_matrix <- cor(data[, c("var1", "var2", "var3", "var4")],
                  use = "pairwise.complete.obs")

# Format lower triangle
cor_matrix[upper.tri(cor_matrix)] <- NA

as.data.frame(cor_matrix) |>
  tibble::rownames_to_column("Variable") |>
  gt() |>
  fmt_number(decimals = 2) |>
  sub_missing(missing_text = "") |>
  tab_header(title = "Table 3", subtitle = "Correlation Matrix")

Expected: A lower-triangle correlation matrix rendered as a gt table with blanked upper triangle, two decimal places, and a clear caption.

On failure: If sub_missing() does not blank the upper triangle, verify that NA values were set correctly with cor_matrix[upper.tri(cor_matrix)] <- NA. If variables are non-numeric, cor() will fail; filter to numeric columns first.

Step 5: ANOVA Table

aov_result <- aov(score ~ group * condition, data = data)

library(gtsummary)

tbl_anova <- broom::tidy(aov_result) |>
  gt() |>
  fmt_number(columns = c(sumsq, meansq, statistic), decimals = 2) |>
  fmt_number(columns = p.value, decimals = 3) |>
  cols_label(
    term = "Source",
    df = md("*df*"),
    sumsq = md("*SS*"),
    meansq = md("*MS*"),
    statistic = md
    p.value  md
   
  tab_headertitle   subtitle  

Expected: A formatted ANOVA table with Source, df, SS, MS, F, and p columns. Interaction terms are clearly labeled and p-values are formatted to three decimal places.

On failure: If broom::tidy(aov_result) produces unexpected columns, verify the model is an aov object. For Type III sums of squares, use car::Anova(model, type = 3) instead of base aov().

Step 6: Save Tables

# Save as HTML
gtsave(my_table, "table1.html")

# Save as Word
gtsave(my_table, "table1.docx")

# Save as PNG image
gtsave(my_table, "table1.png")

# For LaTeX/PDF (kableExtra)
kableExtra::save_kable(kable_table, "table1.pdf")

Expected: Table saved to the specified file format (HTML, Word, PNG, or PDF). The output file opens correctly in the appropriate application.

On failure: If gtsave() fails for Word format, ensure the webshot2 package is installed. For PDF output via kableExtra, ensure a LaTeX distribution (TinyTeX or MiKTeX) is installed.

Step 7: Embed in Quarto Document

```{r}
#| label: tbl-descriptives
#| tbl-cap: "Descriptive Statistics by Group"

gt(descriptives) |>
  fmt_number(columns = c(M, SD), decimals = 2)
```

See @tbl-descriptives for summary statistics.

Expected: The table renders inline in the Quarto document with a cross-referenceable label (@tbl-*) and a proper caption. The table adapts to the document's output format automatically.

On failure: If the table does not render, verify the chunk label starts with tbl- for Quarto cross-referencing. If formatting is lost in PDF, switch from gt to kableExtra for LaTeX-based output.

Validation

• Table renders correctly in target format (HTML, PDF, Word)
• Numbers are formatted consistently (decimal places, alignment)
• Statistical notation follows the style guide (italicized, proper symbols)
• Table has a clear caption and numbering
• Column headers are meaningful
• Notes/footnotes explain abbreviations or significance markers

Common Pitfalls

• gt in PDF: gt has limited PDF support. Use kableExtra for LaTeX-heavy documents.
• Rounding inconsistency: Always use fmt_number() (gt) or format() rather than round() for display
• Missing values display: Configure with sub_missing() in gt or options(knitr.kable.NA = "")
• Wide tables in PDF: Tables exceeding page width need landscape() or font size reduction
• APA number formatting: No leading zero for values bounded by 1 (p-values, correlations): ".03" not "0.03"

Related Skills

• format-apa-report - tables within APA manuscripts
• create-quarto-report - embedding tables in reports
• build-parameterized-report - tables that adapt to parameters